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Unframe is an AI-first startup helping enterprises deploy LLM-powered applications rapidly. The company has secured over $100M in TCV within 12 months and raised a $50M Series B led by Highland Europe, backed by Bessemer, Craft, and TLV.
As Bookkeeper, you will own day-to-day accounting operations and ensure accurate financial records across global operations. This is a hands-on role combining full-cycle bookkeeping with a focus on leveraging AI tools to streamline processes and reduce manual work.
Key responsibilities:
- Own the full bookkeeping cycle: journal entries, accounts payable/receivable, bank reconciliations
- Manage accounting operations using NetSuite, Mesh, and Dokka
- Handle vendor payments, employee expenses, payroll reconciliations, and intercompany transactions
- Manage monthly closing activities including accruals, prepaid expenses, and account reconciliations
- Prepare VAT reports and support statutory reporting and annual audits
- Collaborate with internal teams, external accountants, and auditors
- Improve and scale bookkeeping processes using AI tools such as Claude to increase efficiency
Requirements:
- 3+ years hands-on experience in full-cycle bookkeeping, including month-end closing and financial reconciliations
- Hands-on experience with NetSuite, Mesh, and Dokka
- Previous experience in a technology company or startup, with ability to independently manage end-to-end accounting operations
- Strong proficiency in AI tools such as Claude, with demonstrated experience applying AI to day-to-day work and improving operational efficiency
- Solid understanding of accounting principles, financial controls, and reporting requirements
- Advanced Excel/Google Sheets skills and strong English communication skills
- High level of ownership, accuracy, and ability to work independently in a fast-paced environment
Nice to have:
- Experience working in a global, multi-entity environment with intercompany transactions and reconciliations
- Experience with MCP integrations and connecting AI tools to external systems
